5 best YouTube channels on machine learning

YouTube Channels on Machine Learning

YouTube channels are often the go-to place whenever we need to know something or learn something new. Here are the 5 best YouTube channels for machine learning that you can visit.

Sentdex

Subscribers: 10.6 lakh

Harrison Kinsley, owner of Sentdex YouTube channel, educates people on various technologies including Python programming, web development, machine learning, and more. If you want to learn the workflow of each algorithm like updating bias and intercept in each epoch, or how to implement a given machine learning algorithm from scratch, you need to check the following series done by Harrison Kinsley himself.

Machine learning with Phil

Followers: 24.3k

Phil Tabor is a machine learning engineer who creates educational videos in the field of machine learning and deep learning. He has created a great reading list for Deep Reinforcement Learning Tutorials where he teaches basic reinforcement learning concepts such as Deep Deterministic Policy Gradients in TensorFlow 2, Soft Actor Reviews in PyTorch, robotic control with TD3, and many more.

Two-minute documents

Subscribers: 10.4 lakh

Two Minute Papers is a great channel for anyone who likes to stay up to date with the latest research being done in the field of machine learning. Two Minute Papers makes 2 minute (almost) long videos explaining a research paper. If you are passionate about the field of research, you might want to check out the following series.

Kaggle

Subscribers: 88.1k

The Kaggle Channel is a YouTube spot where you can dive into the world of the Kaggle community, learn, and do your data science work. The channel offers videos with interviews with data scientists, lessons and expert advice. It is one of the best machine learning YouTube channels for anyone who wants to learn tips, experiment and implement new practices in their own work, no matter what environment you work in.

Jeremy Howard

Subscribers: 56k

Jeremy Howard is a data scientist with a background in philosophy, but later, out of curiosity, he harnessed the knowledge of statistics and programming to create the most efficient and easy-to-use library for students. deep learning tasks.

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